Thesiss

The computing needs and the input and result datasets of modern scientific and enterprise applications are growing exponentially. To support such applications, High-Performance Computing (HPC) systems need to employ thousands of cores and innovative data management. At the same …

Support Vector Machines are a machine learning approach that is well studied, thoroughly vetted and effective in a large number of applications. The objective of this thesis is to accelerate an implementation of Support Vector Machines (SVM) using a heterogeneous computing syste…

Large-scale heterogeneous distributed computing environments (such as Computational Grids and Clouds) offer the promise of access to a vast amount of computing resources at a relatively low cost. In order to ease the application development and deployment on such complex environ…